Modeling the Type Hierarchy in High-Dimensional Box Space for Fine-Grained Entity Typing
Yixiu Qin, Feng Wang, Jiawei Li, Yuanfei Deng, Shun Mao, Yuncheng Jiang · IEEE Transactions on Computational Social Systems · 2024
A critical component of fine-grained entity typing is the existence of precise relationship between entity types, such as type hierarchy. Previous approaches for fine-grained entity typing typically model the type hierarchy in vector space, which causes it extremely hard to precisely capture the complex relationship between entity types. To overcome the challenge of modeling type hierarchy in vector space, this article proposes for the first time to model the type hierarchy in high-dimensional box space. In addition, previous approaches focus more on the influence of the context of entity mentions, while neglecting the influence of entity mentions themselves. Based on the above challenges, we present a new approach called THBox, which not only successfully boosts the influence of entity mentions but also models the type hierarchy well. To verify the effectiveness of the method presented in this article, experimental results on three publicly available fine-grained entity typing benchmark datasets are provided to verify that the presented method is a new state-of-the-art solution for fine-grained entity typing.